Telecom

Linear antenna arrays exhibit radiation patterns that are restricted to a half-space and feature axial radiation, which can be a significant drawback for applications that require omnidirectional coverage. To address this limitation, the synthesis method utilizing the Taguchi approach, originally designed for linear arrays, can be effectively extended to two-dimensional or planar antenna arrays. In the context of a linear array, the synthesis process primarily involves determining the feeding law and/or the spatial distribution of the elements along a single axis. Conversely, for a planar array, the synthesis becomes more complex, as it requires the identification of the complex weighting of the feed and/or the spatial distribution of sources across a two-dimensional plane. This adaptation to planar arrays is facilitated by substituting the direction $\theta$ with the pair of directions $(\theta ,\varphi )$, allowing for a more comprehensive coverage of the angular domain. This article focuses on exploring various configurations of planar arrays, aiming to enhance their performance. The primary objective of these configurations is often to minimize the levels of secondary lobes and/or array lobes while enabling a full sweep of the angular space. Secondary lobes can significantly impede system performance, particularly in multibeam applications, where they restrict the minimum distance for frequency channel reuse. This restriction is critical, as it affects the overall efficiency and effectiveness of communication systems that rely on precise beamforming and frequency allocation. By investigating alternative planar array designs and their synthesis methods, this research seeks to provide solutions that improve coverage, reduce interference from secondary lobes, and ultimately enhance the functionality of antennas in diverse applications, including telecommunications, radar systems, and wireless communication. Full article

This paper introduces a novel approach to blind adaptive equalization for digital communication systems using genetic algorithms (GAs). Unlike traditional methods that rely on linear programming and suffer from local minima issues, this technique utilizes a stochastic linear programming cost function with GAs for robust optimization. The proposed method termed Blind Linear Equalizer based on genetic algorithm (BLE-GA) enhances performance by leveraging a GA’s ability to handle stochastic variables, offering rapid convergence and resilience against signal noise and inter-symbol interference. Extensive simulations demonstrate the effectiveness of BLE-GA across different QAM systems, outperforming conventional techniques like the Constant Modulus Algorithm in scenarios with high modulation levels. This study validates the potential of using GAs in adaptive blind equalization to achieve reliable and efficient communication, even in complex and noisy channel conditions. Full article

This article studies the performance of the copper wire communication channel in the existence of the Middleton impulsive noise model. Differential chaos shift keying (DCSK) scheme is implemented with a noise reduction (NR) technique to mitigate the impulsive noise effect and improve system performance. The proposed communication system is simulated using Monte Carlo simulation using MATLAB 2023 and the result is compared with the derived theoretical performance. The use of NR technique in accordance with the proposed model has improved the performance and promoted its use with G.fast Communication. Full article

Integrated Sensing and Communication (ISAC) systems have emerged as a key component for Sixth Generation (6G) networks, enhancing resource efficiency and enabling diverse applications. Currently, ISAC systems have been recognized as a leading trend for future standardization, i.e., International Mobile Telecommunications (IMT)-2030. As in the previous IMT-2020 standardization, the emphasis has been on developing a methodology for assessing network conditions, with one of the crucial approaches incorporating system-level simulations. However, within this framework, there has been a notable absence of proposed abstractions for the physical layer of ISAC systems, which are valuable for system-level simulators. The physical abstraction process helps reduce computational simulation costs, enabling efficient and rapid evaluation of system conditions. Therefore, this paper aims to fill this gap by outlining the key aspects and metrics recommended for a physical layer abstraction in sensing applications within ISAC frameworks. Applying physical abstraction in the context of target localization and detection algorithms may enable an initial understanding and evaluation of ISAC system performance. These algorithms are proposed as an example of simulating the sensing functionalities to be abstracted, which are based on a stochastic geometric channel model. Orthogonal Frequency Division Multiplexing (OFDM) symbols play a crucial role in target position estimation. The findings show that doubling OFDM symbols improves the detection probability by 3 dB in terms of Signal to Noise Ratio (SNR). Finally, the proposed Physical Layer Abstraction (PLA) method produces performance metrics as figures and lookup tables tailored for system-level simulators. Full article

This review provides a comprehensive analysis of the design, materials, fabrication techniques, and applications of flexible wearable antennas, with a primary focus on their roles in Wireless Body Area Networks (WBANs) and healthcare technologies. Wearable antennas are increasingly vital for applications that require seamless integration with the human body while maintaining optimal performance under deformation and environmental stress. Return loss, gain, bandwidth, efficiency, and the SAR are some of the most important parameters that define the performance of an antenna. Their interactions with human tissues are also studied in greater detail. Such studies are essential to ensure that wearable and body-centric communication systems perform optimally, remain safe, and are in compliance with regulatory standards. Advanced materials, including textiles, polymers, and conductive composites, are analyzed for their electromagnetic properties and mechanical resilience. This study also explores innovative fabrication techniques, such as inkjet printing, screen printing, and embroidery, which enable scalable and cost-effective production. Additionally, solutions for SAR optimization, including the use of metamaterials, electromagnetic band gap (EBG) structures, and frequency-selective surfaces (FSSs), are discussed. This review highlights the transformative potential of wearable antennas in healthcare, the IoT, and next-generation communication systems, emphasizing their adaptability for real-time monitoring and advanced wireless technologies, such as 5G and 6G. The integration of energy harvesting, biocompatible materials, and sustainable manufacturing processes is identified as a future direction, paving the way for wearable antennas to become integral to the evolution of smart healthcare and connected systems. Full article

Applying optimal power control techniques in wireless networks is invaluable to mitigating interference among mobile devices. This review seeks to evaluate the depth and extent of the application of power control in 5G wireless networks through a systematic literature review. This review includes journal articles from 2018 to 2023 indexed in the Scopus, Web of Science (WoS), and IEEE Xplore databases. We used the following search string to search articles from each database: (*power control” AND “resource management” OR interference management AND 5G mobile communication). We obtained 3561 articles from the Scopus, WoS, and IEE Xplore databases with respective counts of 254, 728, and 2579. We paid attention to journal articles to ensure the quality of the review. After carefully assessing each record, we selected 770 journal articles using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Using R package software, we performed analyses based on the number of citations, keyword co-occurrence, and trending topics. This review reveals that various power control taxonomies address interference in 5G wireless networks. The results confirm continuous growth in the study, signifying the need for further exploration. Full article

This paper examines two-way relaying cognitive radio networks utilizing fountain coding (FC), reconfigurable intelligent surfaces (RIS), and radio frequency energy harvesting (EH). In the proposed schemes, two secondary sources attempt to exchange data with each other through the assistance of an RIS deployed in the network. Using FC, one source sends its encoded packets to the other source, which must collect enough packets for a successful data recovery. The transmit power of the two sources is adjusted according to an interference constraint given by a primary user and the energy harvested from a power station. In the conventional scheme, one source continuously transmits FC packets to the other, using the maximum number of transmissions allowed. In the modified scheme, as soon as one source collects a sufficient number of FC packets, it notifies the other source to stop transmission. We derive closed-form expressions of outage probability (OP) at each source, system outage probability (SOP), and average number of FC-packet transmissions for the successful data exchange of the considered schemes over Rayleigh fading channels. Simulation results are provided to validate our analysis, to compare the performance of the considered schemes, and to examine the impact of key parameters on performance. Full article

Efficient Virtual Machine (VM) placement is a critical challenge in optimizing resource utilization in cloud data centers. This paper explores both exact and approximate methods to address this problem. We begin by presenting an exact solution based on a Multi-Objective Integer Linear Programming (MOILP) model, which provides an optimal VM Placement (VMP) strategy. Given the NP-completeness of the MOILP model when handling large-scale problems, we then propose an approximate solution using a Tabu Search (TS) algorithm. The TS algorithm is designed as a practical alternative for addressing these complex scenarios. A key innovation of our approach is the simultaneous optimization of three performance metrics: the number of accepted VMs, resource wastage, and power consumption. To the best of our knowledge, this is the first application of a TS algorithm in the context of VMP. Furthermore, these three performance metrics are jointly optimized to ensure operational efficiency (OPEF) and minimal operational expenditure (OPEX). We rigorously evaluate the performance of the TS algorithm through extensive simulation scenarios and compare its results with those of the MOILP model, enabling us to assess the quality of the approximate solution relative to the optimal one. Additionally, we benchmark our approach against existing methods in the literature to emphasize its advantages. Our findings demonstrate that the TS algorithm strikes an effective balance between efficiency and practicality, making it a robust solution for VMP in cloud environments. The TS algorithm outperforms the other algorithms considered in the simulations, achieving a gain of 2% to 32% in OPEF, with a worst-case increase of up to 6% in OPEX. Full article

The proliferation of drones in civilian environments has raised growing concerns about their misuse, highlighting the need to develop efficient detection systems to protect public and private spaces. This article presents a hybrid approach for UAV detection that combines two artificial-intelligence-based methods to improve system accuracy. The first method uses a software-defined radio (SDR) to analyze the radio spectrum, employing autoencoders to detect drone control signals and identify the presence of these devices. The second method is a computer vision module consisting of fixed cameras and a PTZ camera, which uses the YOLOv10 object detection algorithm to identify UAVs in real time from video sequences. Additionally, this module integrates a localization and tracking algorithm, allowing the tracking of the intruding UAV’s position. Experimental results demonstrate high detection accuracy, a significant reduction in false positives for both methods, and remarkable effectiveness in UAV localization and tracking with the PTZ camera. These findings position the proposed system as a promising solution for security applications. Full article

The vision of the sixth generation of communication systems, commonly known as 6G, entails a connected world that provides ubiquitous connectivity and fosters the digital transformation of society. As the number of devices, services, and users continues to grow, intelligent solutions are expected to facilitate this transformation. This paper considers meta-learning as a pivotal paradigm for 6G systems, detailing its principles, algorithms, and theoretical underpinnings. The methodology involves integrating meta-learning with three potential 6G technologies: RF-based communication systems, optical communication systems, and molecular communication systems. The findings reveal the distinct characteristics of these technologies and demonstrate the potential benefits and challenges of incorporating meta-learning algorithms. Practical implications highlight how meta-learning can enhance the efficiency and adaptability of 6G systems, addressing the growing demand for intelligent and seamless communication networks. Full article

This paper presents a unified performance metric for evaluating the chronological wild geese optimization (CWGO) algorithm in wireless sensor networks (WSNs). The metric combines key performance factors—energy consumption, delay, distance, and trust—into a single measure using Lagrange interpolation, providing a more comprehensive assessment of WSN algorithms. We evaluate CWGO against E-CERP, EECHIGWO, DUCISCA, and DE-SEP across static and dynamic sensor node configurations in various wireless technologies, including LoRa, Wi-Fi, Zigbee, and Bluetooth low energy (BLE). The results show that CWGO consistently outperforms the other algorithms, especially in larger node configurations, demonstrating its scalability and robustness in static and dynamic environments. Moreover, the unified metric reveals significant performance gaps with EECHIGWO, which underperforms all wireless technologies. DUCISCA and DE-SEP show moderate and fluctuating results, underscoring their limitations in larger networks. While E-CERP performs competitively, it generally lags behind CWGO. The unified metric offers a holistic view of algorithm performance, conveying clearer comparisons across multiple factors. This study emphasized the importance of a unified evaluation approach for WSN algorithms and positions CWGO as a superior solution for efficient cluster head selection and routing optimization in diverse WSN scenarios. While CWGO demonstrates superior performance in simulation, future research should validate these findings in real-world deployments, accounting for hardware limitations and in a highly dynamic environment. Further optimization of the unified metrics’ computational efficiency could enhance its real-time applicability in larger, energy-resource-constrained WSNs. Full article

Digital terrestrial television is now implemented in many countries worldwide and is now mature. Digital Video Broadcasting-Terrestrial, second generation (DVB-T2) is the European standard adopted or deployed by European and African countries which uses Orthogonal Frequency-Division Multiplexing (OFDM) modulation to achieve good throughput performance. However, its main particularity is the number of subcarriers operated for OFDM modulation which varies from 1024 to 32,768 subcarriers. Also, mobile reception is planned in DVB-T2 in addition to rooftop antenna and portable receptions planned in DVB-T. However, the main challenge of DVB-T2 for mobile reception is the presence of a carrier frequency offset (CFO) which degrades the system performance by inducing an Intercarrier Interference (ICI) on the DVB-T2 signal. This paper evaluates the system performance in the presence of the CFO when Gaussian noise and a TU6 channel are applied. Universal Filtered Multicarrier (UFMC) and non-uniform constellations (NUCs) have previously demonstrated good performance in comparison with OFDM and Quadrature Amplitude Modulation (QAM) in DVB-T2. The impact of CFO on the UFMC- and NUC-based DVB-T2 system is additionally investigated in this work. The results demonstrate that the penalties induced by CFO insertion in UFMC- and NUC-based DVB-T2 are highly reduced in comparison to those for the native DVB-T2. At a bit error rate (BER) of ${10}^{-3}$, the CFO penalties induced by the native DVB-T2 are $0.96$$\mathrm{d}$$\mathrm{B}$ and 4 $\mathrm{d}$$\mathrm{B}$, respectively, when only Additive White Gaussian Noise (AWGN) is used and when TU6 is additionally considered. The penalties are equal to $0.84$$\mathrm{d}$$\mathrm{B}$ and $0.2$$\mathrm{d}$$\mathrm{B}$ for UFMC/NUC-based DVB-T2. Full article

This paper addresses the problem of side lobe interference in 5G networks by proposing a unique collaborative beamforming strategy based on Deep Q-Network (DQN) reinforcement learning. Our method, which operates in the sub-6 GHz band, maximizes beam steering and power management by using a two-antenna system with DQN-controlled phase shifters. We provide an OFDM cellular network environment where inter-cell interference is managed while many base stations serve randomly dispersed customers. In order to reduce interference strength and improve signal-to-interference-plus-noise ratio (SINR), the DQN agent learns to modify the interference angle. Our model integrates experience replay memory with a long short-term memory (LSTM) recurrent neural network for time series prediction to enhance learning stability. The outcomes of our simulations show that our suggested DQN approach works noticeably better than current DQN and Q-learning methods. In particular, our technique reaches a maximum of 29.18 dB and a minimum of 5.15 dB, whereas the other approaches only manage 0.77–27.04 dB. Additionally, we significantly decreased the average interference level to 5.42 dB compared to competing approaches of 38.84 dB and 34.12 dB. The average sum-rate capacity is also increased to 3.90 by the suggested strategy, outperforming previous approaches. These findings demonstrate how well our cooperative beamforming method reduces interference and improves overall network performance in 5G systems. Full article

This research aims to evaluate the reliability indices of a public address system (PAS) through the Markovian approach. Many organizations and businesses use this system to address or broadcast a message or pass on important information to the huge gatherings assembled at big premises. This system is the nerve of these organizations and businesses. The major components of a PAS are a microphone, mixer, amplifier, and speaker. These components should work in harmony with one another to execute the intended task. Any failure in these components leads to big issues for the public, and they may miss very important information. Therefore, the reliability assessment of this system is of utmost importance. The authors used the Markovian decision process to model the PAS by analyzing the various failure rates and repairs of the components. The explicit expressions for reliability, availability, and MTTF have been obtained for clear understanding about the PAS behavior with time as well as different failures. The sensitivity analysis of reliability is performed as well to determine the critical components of the system. The obtained results show that the reliability of the PAS at 2000 operated hours is 0.8. Also, the finding reflects that the PAS reliability is much sensitive with the failure rate of microphone, mixer, and amplifier. Full article

In the past few years, one of the largest industries in the world, the agriculture sector, has faced many challenges, such as climate change and the depletion of limited natural resources. Smart Agriculture, based on IoT, is considered a transformative force that will play a crucial role in the further advancement of the agri-food sector. Furthermore, in IoT-based Smart Agriculture systems, radio wave propagation faces unique challenges (such as attenuation in vegetation and soil and multiple reflections) because of sensor nodes deployed in agriculture fields at or slightly above the ground level. In our study, we present, for the first time, several models (Multi-slope, Weissberger, and COST-235) suitable for planning radio coverage in a cornfield for Smart Agriculture applications. We received signal level measurements as a function of distance in a corn field (R3 corn stage) at 0.9 GHz and 2.4 GHz using two transmitting and two receiving antenna heights, with both horizontal and vertical polarization. The results indicate that radio wave propagation in a corn field is influenced not only by the surrounding environment (i.e., corn), but also by the antenna polarization and the positions of the transmitting and receiving antennas relative to the ground. Full article

The intense diversity of the Next-Generation Networking environments like 6G and the forthcoming deployment of immersive applications with varied user-specific requirements transform the efficient allocation of resources into a real challenge. Traditional solutions like the shortest path algorithm and mono-constraint methodologies are inadequate to handle customized user-defined performance parameters and effectively classify physical resources according to these intricate demands. This research offers a new evaluation mechanism to successfully replace the aforementioned traditional path ranking and path selection techniques. Specifically, the proposed framework is integrated with optimization-oriented metrics, each indicating a unique aspect of performance for evaluating candidate network paths. The deployed metrics are then algebraically synthesized to provide a distinctive multidimensional description of the examined substrate resources. These primary and composite metrics adhere to the fundamental monotonicity and isotonicity properties of a Path Algebra; hence, the validity and optimality of the proposed evaluation mechanism is guaranteed by design. To tackle the complexity created by the variety of human-centric customization, a novel methodology that analyzes and determines the weighted influence of the synthesized metrics depending on the characteristics of the served user-centric application is also introduced. The chosen suitable weights address performance-oriented mission-critical tailored objectives for adaptive optimizations. Its innovative algebraic design allows it to successfully describe and rank candidate paths in a versatile way, whether in legacy or modern architectures. The experimental data of the first scenario show that 62.5% and 50% of highlighted path evaluations proposed by the shortest path and unidimensional constraint strategies, respectively, suffer from moderate performance-oriented values compared to the proposed framework. Likewise, the results of the second examined scenario reveal that the proposed composite metric yields more suitable path rankings by 50% in contrast to its traditional counterparts, rendering the contested evaluation mechanisms obsolete. Full article

This paper aims to provide a general review of the fundamental ideas, varieties, methods, and experimental research of the most advanced frequency selective surfaces available today. Frequency-selective surfaces are periodic structures engineered to work as spatial filters in interaction with electromagnetic (EM) waves with different frequencies, polarization, and incident angles in a desired and controlled way. They are usually made of periodic elements with dimensions less than the operational wavelength. The primary issue examined is the need for more efficient, compact, and adaptable electromagnetic filtering solutions. The research method involved a comprehensive review of recent advancements in FSS design, focusing on structural diversity, miniaturization, multiband operations, and the integration of active components for tunability and reconfigurability. Key findings include the development of highly selective miniaturized FSSs, innovative applications on flexible and textile substrates, and the exploration of FSSs for liquid and strain sensing. The conclusions emphasize the significant potential of FSS technology to enhance wireless communication, environmental monitoring, and defense applications. This study provides valuable insights into the design and application of FSSs, aiming to guide future research and development in this dynamic field. Full article

This work presents an in-depth evaluation of the telecommunications landscape in Mexico from 2015 to 2023. The study’s primary focus is on the disparities in broadband access, telecommunications infrastructure, and digital inclusion across various regions, particularly between urban and rural areas. By employing predictive models and correlation analysis, the paper identifies key factors influencing technology adoption and service bundling in households. A significant contribution of this research lies in its identification of strong correlations between broadband access, GDP growth, and the penetration of multiple telecommunication services such as fixed telephony, broadband internet, and television. The predictive models developed offer crucial insights into the regional inequalities of digital access, revealing patterns that policymakers can use to prioritize infrastructure investments. The findings underscore the essential role of public policy innovation in promoting digital inclusion, particularly in underdeveloped regions, and provide a robust analytical framework for understanding how advanced telecommunications services contribute to socio-economic development. Through this analytical approach, the study demonstrates the critical relationship between telecommunications infrastructure and regional economic performance, offering data-driven recommendations to bridge the digital divide and enhance connectivity in underserved areas. The results offer significant value for future research and policy initiatives aimed at fostering equitable access to Information and communication technologies, promoting economic growth, and ensuring broader societal inclusion in the digital age. Full article

This study presents a novel approach to enhancing the design and performance of OFDMA (Orthogonal Frequency Division Multiple Access) networks, with a particular focus on WiMAX (Worldwide Interoperability for Microwave Access) for Best Effort (BE) services. The proposed method integrates a robust Markovian analytical model with four advanced scheduling algorithms: throughput fairness, resource fairness, opportunistic scheduling, and throttling. A sophisticated simulator was developed, incorporating an ON/OFF traffic generator, user-specific wireless channels, and a dynamic central scheduler to validate the model’s accuracy and evaluate its robustness by dynamically allocating radio resources per frame. The validation study showed that the proposed model reduced simulation time by over 90%, completing analytical calculations in just 15 min, compared to nearly 2 days for simulations using conventional scheduling algorithms. Performance metrics such as the average number of active users and resource utilization closely matched those from the validation study, confirming the model’s accuracy. In the robustness study, the model consistently performed well across diverse traffic distributions (exponential and Pareto) and channel conditions. The proposed architecture increased network throughput by up to 25% and reduced latency under dynamic conditions, demonstrating its scalability, adaptability, and efficiency as a crucial solution for next-generation wireless communication systems. Full article